Recent advances in Generative Artificial Intelligence (GenAI) have significantly transformed the way knowledge is created, interpreted, and applied across multiple disciplines. Technologies such as generative adversarial networks (GANs), diffusion models, large language models, and multimodal generative systems are enabling new forms of creativity, problem solving, and innovation in education, design, and complex engineering domains. These technologies are increasingly being integrated into intelligent learning environments, automated design systems, engineering optimization frameworks, and decision-support tools, thereby reshaping traditional workflows and expanding the boundaries of human computer collaboration.

This Special Issue aims to explore emerging methodologies, applications, and theoretical perspectives related to GenAI and its role in enhancing creativity and innovation. The issue will focus on novel frameworks, algorithms, and systems that leverage generative models to address real-world challenges in education, digital design, and engineering systems. Topics of interest include research on generative models for intelligent tutoring, AI-assisted creative design, generative optimization in engineering systems, and human-centered AI approaches that augment creativity and productivity.

By bringing together interdisciplinary research from artificial intelligence, education technology, computational design, and engineering innovation, this Special Issue seeks to provide insights into how GenAI can support next generation creative and intelligent systems. The goal is to enhance collaboration between researchers and practitioners while highlighting cutting edge developments that shape the future of AI-driven innovation.